Prognostic role of body composition parameters in gastric/gastroesophageal junction cancer patients from the EXPAND trial

Abstract

Background: Body fat and/or muscle composition influences prognosis in several cancer types. For advanced gastric and gastroesophageal junction cancer, we investigated which body composition parameters carry prognostic information beyond well-established clinical parameters using robust model selection strategy such that parameters identified can be expected to generalize and to be reproducible beyond our particular data set. Then we modelled how differences in these parameters translate into survival outcomes.

Methods: Fat and muscle parameters were measured on baseline computed tomography scans in 761 patients with advanced gastric or gastroesophageal junction cancer from the phase III EXPAND trial, undergoing first-line chemotherapy. Cox regression analysis for overall survival (OS) and progression-free survival (PFS) included body composition parameters and clinical prognostic factors. All continuous variables were entered linearly into the model as there was no evidence of non-linear prognostic impact. For transferability, the final model included only parameters that were picked by Bayesian information criterion model selection followed by bootstrap analysis to identify the most robust model.

Results: Muscle and fat parameters formed correlation clusters without relevant between-cluster correlation. Mean muscle attenuation (MA) clusters with the fat parameters. In multivariate analysis, MA was prognostic for OS (P < 0.0001) but not for PFS, while skeletal muscle index was prognostic for PFS (P = 0.02) but not for OS. Worse performance status Eastern Cooperative Oncology Group (ECOG 1/0), younger age (on a linear scale), and the number of metastatic sites were strong negative clinical prognostic factors for both OS and PFS. MA remained in the model for OS (P = 0.0001) following Bayesian information criterion model selection in contrast to skeletal muscle index that remained prognostic for PFS (P = 0.009). Applying stricter criteria for transferability, MA represented the only prognostic body composition parameter for OS, selected in >80% of bootstrap replicates. Finally, Cox model-derived survival curves indicated that large differences in MA translate into only moderate differences in expected OS in this cohort.

Conclusions: Among body composition parameters, only MA has robust prognostic impact for OS. Data suggest that treatment approaches targeting muscle quality are unlikely to prolong OS noticeably on their own in advanced gastric cancer patients, indicating that multimodal approaches should be pursued in the future.

Keywords: Computed tomography; Gastric cancer; Gastroesophageal junction cancer; Mean muscle attenuation; Prognosis; Sarcopenia; Smooth muscle index.

Figure 1

Graphical correlation matrix of body mass index (BMI) and fat/muscle‐related body composition parameters. Green lines indicate positive correlations; blue lines indicate negative correlations. Thickness of line indicates strength of the correlation (corresponding numerical values: see Table S1). Mpso, psoas muscle; Mspi, spinal muscle; Mven, ventral abdominal muscle; SAT, subcutaneous adipose tissue; SMI, skeletal muscle index; TAT, total adipose tissue; VAT, visceral adipose tissue.

Figure 2

Cox model‐derived survival curves generated for covariate constellations of interest: ECOG PS (0/1), MA, and age fixed at their 20% and 80% quintiles, respectively. OS, overall survival.